Implementasi Algoritma K-Medoids dalam Pengelompokan Mahasiswa yang Layak Mendapat Bantuan Uang Kuliah Tunggal
(Studi Kasus: Universitas Budi Darma)
DOI:
https://doi.org/10.55123/insologi.v1i2.195Keywords:
K-Medoids Algorithm Implementation, Clustering, Single Tuition Assistance (UKT), Budi Darma UniversityAbstract
The Single Tuition Assistance Program (UKT) is a program aimed at students whose parents' jobs have been affected by COVID-19. Where this assistance is a program from the government to reduce the number of students who stop continuing their education due to the impact of income during Covid-19, so that universities are appointed by the government to select students who deserve the assistance. However, the problem is, the manual selection system can cause errors or confusion in making the selection so that the term wrong target arises. To narrow this possibility, these problems can be overcome by using data mining to assist universities in determining students who deserve single tuition assistance (UKT). In data mining, a method is needed. In this research, clustering method is used using the K-Medoids Algorithm so that decision making is very effective and fast. Based on this research, it is known that those who deserve to receive tuition assistance in arrears (UKT) are Rohan Purba, Zaza Mutiara, Putri and Alexander.
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Copyright (c) 2022 Efori Bu'ulolo, Rohan Kristini Purba
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